
The query simplifier can then be applied to the ad hoc search sessions (e.g., MS MARCO) to generate more conversation-like sessions.
[1]} find that it is easier to train a query simplifier (Equation REF ) that learns to omit information from an ad hoc query using session context than to train a query rewriter (Equation REF ) that learns to recover the omitted information. Empirically, the weak-supervision data generated using the machine learning approach significantly boosts the performance of the GPT-2 based query rewriter on the TREC CAsT benchmarks.
